most citedAttention Is All You Need But You Don't Need All Of It For Inference of Large Language Models

3 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

stat.ML2026

Soft Specialists: -Rényi Ensembles for Uncertainty-Aware LLM Post-Training

Paula Cordero-Encinar, Georgy Tyukin, Andrew B. Duncan

Existing training approaches for large language models learn a single set of parameters, based on large volumes of data, which is typically heterogeneous, conflicting and often out…

cs.LG2024★ 3 cited

Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models

Georgy Tyukin, Gbetondji J-S Dovonon, Jean Kaddour +1

The inference demand for LLMs has skyrocketed in recent months, and serving models with low latencies remains challenging due to the quadratic input length complexity of the attent…

cs.LG2024

Enhancing Inference Efficiency of Large Language Models: Investigating Optimization Strategies and Architectural Innovations

Georgy Tyukin

Large Language Models are growing in size, and we expect them to continue to do so, as larger models train quicker. However, this increase in size will severely impact inference co…